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Fuzzy-Based Satellite Image classification to find Greenery and Used Land

N. Suresh Kumar, S. Margret Anouncia, M. Prabu


This research work describes the region based approach for satellite image classification to extract Land use details for the agriculture in Vellore region. The objective is to find the Greenery and used lands of study area by classify the satellite imagery using Fuzzy-based supervised classification method and spectral information of an LANDSAT satellite image. The LANDSTSAT Image is applied with improved image processing technique to get the image of classification. The satellite image is segmented into regions using decorrelation in fuzzy fication process. The fuzzyfication process also incorporates edge information to avoid intermixing of sub-pixels of remotely sensed images. This fuzzy based classification of satellite image is particularly to find the greenery and the land use of Vellore region. This work gives an overview about this Program and discusses several research issues. First, the remote sensing data sources and other ancillary data used in this work are presented. The approaches for image preprocessing, i.e. clustering, segmentation, classification, correlations are then introduced with an emphasis on the algorithm development for image registration. Second, land use change detection technique is the most critical and complex aspect of the Program. Third, the data of land use changes derived from remote sensing will be operationally used.


Fuzzyfication, Satellite Image Processing, Use land detection, Remote Sensing, GIS.

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